Ching Ching Lau, M.D., Ph.D. - US grants
Affiliations: | Pediatrics, Hematology & Oncology | Baylor College of Medicine, Houston, TX |
Area:
pediatric gliomas, picornavirus SVV-001, medulloblastomaWebsite:
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The funding information displayed below comes from the NIH Research Portfolio Online Reporting Tools and the NSF Award Database.The grant data on this page is limited to grants awarded in the United States and is thus partial. It can nonetheless be used to understand how funding patterns influence mentorship networks and vice-versa, which has deep implications on how research is done.
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High-probability grants
According to our matching algorithm, Ching Ching Lau is the likely recipient of the following grants.| Years | Recipients | Code | Title / Keywords | Matching score |
|---|---|---|---|---|
| 1996 — 2001 | Lau, Ching Ching | P30Activity Code Description: To support shared resources and facilities for categorical research by a number of investigators from different disciplines who provide a multidisciplinary approach to a joint research effort or from the same discipline who focus on a common research problem. The core grant is integrated with the center's component projects or program projects, though funded independently from them. This support, by providing more accessible resources, is expected to assure a greater productivity than from the separate projects and program projects. |
Molecular Biology of Medulloblastoma @ Baylor College of Medicine Neoplasm of the central nervous system (CNS) constitutes the largest group of solid tumors in children and are second only to leukemia and lymphoma in their overall frequency during childhood. The annual incidence is approximately 1500 to 200 with slight increase in the last decade. Medulloblastoma is the most common CNS tumor n children, with approximately 350 to 400 new cases diagnosed in the US each year. Because of the low incidence of this tumor, compared with the adult tumors such as colon or breast carcinoma, very limited basic research has been done to further the understanding of the biology of genetics of medulloblastoma. Despite multi-center clinical trials using increasingly sophisticated neurosurgical and other therapeutic interventions, the majority of the children with advanced medulloblastoma eventually die of progressive disease. Progress in treatment outcome has been hindered primarily by the lack of understanding of the biological properties and the prognostic indicators of these tumors. Recent advances in molecular biology have provided the tools to delineate the various steps of genetic alterations involved in the development of human cancer. Numerous proto-oncogenes and a few tumor suppressor genes have been identified and the specific roles of some of these genes in oncogenesis are becoming clear. In this project, I plan to define some of the basic biological properties and the genetic alterations in medulloblastoma. Specifically, this project will consist of four parts: 1. Establishing a brain tissue bank consisting of both tumor and matched normal tissues obtained at the time of surgery as discarded surgical materials. In addition, brain tissues will also be collected from patients undergoing lobotomy for nonmalignant disease or autopsy. 2. Establishing and characterizing medulloblastoma cell lines and normal brain cell cultures. In addition, normal brain cell cultures will also be immortalized to provide unlimited supply of normal cells for future studies. These tumor and normal cell lines will be characterized in terms of their growth parameters, tumorigenicity in nude mice, potential for differentiation into neuronal or glial cells, karyotype, as well as the effects of various cytokines, growth factors and chemotherapeutic agents on growth, differentiation and cytotoxicity. 3. Defining regions of chromosomal deletion in medulloblastoma by detailed allelotyping using PCR-based microsatellite polymorphic markers. In addition, loss of heterozygosity (LOH) involving known tumor suppressor genes will also be examined and positive results will be followed up by a search for mutations in the remaining allele using single strand conformational polymorphism and DNA sequencing. LOH patterns will be compared between high and low risk medulloblastomas as well as between primary and relapsed tumors to determine if these LOH markers correlate with progression of disease. 4. Identifying differentially expressed genes in medulloblastoma using arbitrarily primed PCR to generate differential RNA fingerprints from normal and medulloblastoma cell lines. Differentially expressed genes found in cell lines will be confirmed by similar studies using RNA from fresh tumors and their matched normal tissues. Focus will be placed on detecting tumor suppressor genes that are expressed in the normal tissues but not in the tumors. Candidates for novel tumor suppressor genes identified through this type of screening will be followed up by gene mapping and positional cloning. |
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| 2001 — 2004 | Lau, Ching Ching | U01Activity Code Description: To support a discrete, specified, circumscribed project to be performed by the named investigator(s) in an area representing his or her specific interest and competencies. |
Molecular Classification of Osteosarcoma @ Baylor College of Medicine DESCRIPTION: (Applicant's Description) Osteosarcoma is the most common malignant bone tumor in children. Approximately 80 percent of patients present with non-metastatic disease. After the diagnosis is made by a biopsy, treatment involves 3-4 courses of neoadjuvant chemotherapy before definitive surgery, followed by post-operative chemotherapy. With currently available treatment, approximately 30-40 percent of patients with non-metastatic disease relapse after therapy. There is no prognostic factor that can be used at the time of diagnosis to predict which patients will have a high risk of relapse. The only significant prognostic factor predicting the outcome in a patient with non-metastatic osteosarcoma is the histopathologic response of the primary tumor resected at the time of definitive surgery. The degree of necrosis in the primary tumor is a reflection of the tumor response to neoadjuvant chemotherapy. Higher degree of necrosis is associated with lower risk of relapse and therefore better outcome. Patients with lower degree of necrosis have a much higher risk of relapse and poor outcome even after complete resection of the primary tumor. Unfortunately this poor outcome cannot be altered despite modification of post-operative chemotherapy to account for the resistance of the primary tumor to neoadjuvant chemotherapy. Thus there is an urgent need to identify prognostic factors that can be used at the time of diagnosis to recognize the subtypes of osteosarcomas patients that have high risk of relapse so that more appropriate chemotherapy can be used at the outset to improve the outcome. We propose to establish a molecular classification system to distinguish such subsets of osteosarcoma based on their gene expression profiles. This project will be a collaboration among several institutions including the Texas Children's Cancer Center, Baylor College of Medicine, Pediatric Oncology Branch, NCI, Cancer Genetics Branch, NHGRI, Biometric Research Branch, NCI and Incyte Pharmaceuticals, Inc. We plan to recruit 100 osteosarcoma patients who are receiving the same therapy through a treatment protocol. Using cDNA microarrays, we will investigate the gene expression profiles of the tumor tissues at the time of biopsy and definitive surgery. These profiles will be correlated with clinical outcome. In addition, we also plan to compare the gene expression profiles of the primary tumor and those of the metastatic lesions. The specific aims are: 1. To validate and optimize cDNA microarray technology for gene expression profiling of clinical specimens. 2. To establish the relevant gene expression profiles for molecular classification of osteosarcoma by correlating these profiles with clinical outcome, chemosensitivity, and metastatic potential. |
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| 2002 — 2007 | Lau, Ching Ching | R21Activity Code Description: To encourage the development of new research activities in categorical program areas. (Support generally is restricted in level of support and in time.) R33Activity Code Description: The R33 award is to provide a second phase for the support for innovative exploratory and development research activities initiated under the R21 mechanism. Although only R21 awardees are generally eligible to apply for R33 support, specific program initiatives may establish eligibility criteria under which applications could be accepted from applicants demonstrating progress equivalent to that expected under R33. |
Genomic Profile-Based Prognostic Markers For Ependymoma @ Baylor College of Medicine DESCRIPTION (provided by applicant): Ependymoma is a neuroepithelial tumor that occurs predominantly in children and young adults, accounting for 8-10 percent of intracranial tumors in children. Despite recent advances in neurosurgery, radiotherapy and chemotherapy, nearly half of the children with intracranial ependymoma eventually die of progressive disease. This unsatisfactory prognosis reflects our poor understanding of the biology of this tumor. Current prognostic factors such as age at diagnosis and degree of surgical resection are inadequate predictors of outcome. Despite claims that the outcome of differentiated and anaplastic ependymoma are different, the influence of histology on prognosis remains controversial. Thus there is an urgent need to identify reliable prognostic markers to provide a more objective and accurate way to classify ependymomas for treatment stratification in multi-institutional clinical trials. One strategy to discover such prognostic markers is to identify genetic alterations that determine the malignant behavior in tumor cells. We have recently developed new approaches to perform comprehensive genetic analysis on pediatric brain tumors by using state-of-the-art genomic technologies. One technique, comparative genomic hybridization (CGH), enables us to create complete profiles of chromosome copy number aberrations (CNAs) in tumors with high efficiency and precision. Our preliminary results with a small number of cases suggest that these profiles identify clinically relevant subgroups of ependymomas. This proposal will expand our study to provide enough statistical power to draw definitive conclusions. At the same time, we are making major modifications to the standard CGH technique by converting it into a high throughput and more sensitive format. Instead of analyzing the aberrations at the level of chromosomes, we are substituting an array of mapped clones of DNA fragments for individual chromosomes. This latest modification greatly improves the precision and efficiency of CGH, produces a precise physical map of the genetic abnormality and will allow the analysis of more samples in less time. This proposal will be the biologic study arm of a new COG Phase II trial for ependymoma (ACNS-0121) approved by CTEP. Our goal is to build a molecular classification system for ependymomas to allow objective patient stratification for future clinical trials. In addition, identifying the genetic abnormalities in ependymomas may ultimately lead to the discovery of new therapeutic targets. |
1.009 |
| 2020 | Casey, Graham (co-PI) [⬀] Lai, Rose Kamyee Lau, Ching Ching |
R01Activity Code Description: To support a discrete, specified, circumscribed project to be performed by the named investigator(s) in an area representing his or her specific interest and competencies. |
Functional Characterization of Glioma Gwas Variants @ University of Southern California PROJECT SUMMARY/ABSTRACT The goal of the proposed study is to discern the functional and biological relevance of gliomas risk variants identified through genome wide association studies (GWAS). GWAS have led to the discovery of 8 susceptibility loci in glioma: 8q24.11, 11q23.3, 5p15.33, 9p21.3, 20q13.33, 7p11.2 (2 independent loci) and 3q26.2. None of the GWAS SNPs map to exons and we hypothesize that the associated SNPs are non- functional, are in linkage disequilibrium with casual/functional SNPs, and map to risk enhancers that in turn regulate target gene expression in an allele specific manner. To date no functional/causal variants for glioma GWAS have been identified. However, our team has identified some candidate target genes for 6 of the 8 GWAS loci using expression quantitative trait loci (eQTL) mapping in multiple brain regions and allelic specific gene expression (ASE) analyses. Based on these promising findings, we propose a comprehensive post GWAS analysis of glioma risk loci using a series of complementary approaches. In Aim 1 we will identify candidate target genes of glioma risk loci using data from two sources: publicly available RNA-Seq and genotyping data from multiple brain regions of 400 post-mortem brains of the Genotype-Tissue Expression Project's (GTEx); we will also generate RNA-Seq and genotyping data from an additional 300 pathologically verified, fresh-frozen autopsied normal brain tissues (multiple brain regions) from the University of Miami Brain Bank (UMBB). eQTL mapping, eQTL meta-analyses and eQTL-ASE will be performed, using the UMBB samples as the discovery set and GTEx dataset as a validation dataset. In Aim 2 we will use publicly available ChIP-Seq and DNAse1 hypersensitivity chromatin data to identify candidate regulatory elements within GWAS loci. We will: (a) validate candidate regulatory elements using enhancer/promoter luciferase vector activity assays in multiple glioma cell lines. (b) Assess allele specific effects on enhancer/promoter activity using either site-directed mutagenesis or naturally occurring haplotypes (c). Identify and validate novel candidate target genes of risk enhancers identified in Aim 1 by knocking out risk enhancers using CRISPR-Cas9 gene editing technology in glioma cell lines and assessing changes in target gene expression using RNA-Seq. In Aim 3 we will use existing data and novel data generated through Aims 1 and 2, to identify and validate the physical interaction between risk enhancers and candidate target genes. Interacting loci of candidate risk enhancers will be identified using 4C-Seq using five glioma cell lines, and will be compared to candidate target genes identified through Aims 1 and Aim 2. Any significant interactions, especially those with candidate local and distal target genes identified through Aims 1 and 2 will be further validated by 3C and fluorescent in situ hybridization (FISH). Through these efforts we will develop a mechanistic and biological understanding of glioma risk that will be an essential first step in our translational efforts to develop preventive therapeutics approaches for glioma. |
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